STAC Summit, 17 October 2024, New York

STAC Summits

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STAC Summits bring together CTOs and other industry leaders responsible for solution architecture, infrastructure engineering, application development, machine learning/deep learning engineering, data engineering, and operational intelligence to discuss important technical challenges in trading and investment.

WHEN
Thursday, October 17, 2024
STAC Exchange (Exhibits) opens at 8:30am EDT
Conference starts at 9:00am EDT
Networking lunch at ~12:00pm EDT
Conference concludes at ~5:00pm EDT
Reception immediately following
WHERE
New York Marriott Marquis
1535 Broadway
New York
Astor Ballroom
7th Floor



Register for the event

Financial Firms
Vendor Members & Sponsors
Others
Technologists from trading organizations, such as banks, brokerages, exchanges, hedge funds, prop shops, asset managers, etc.
Employees from technology member firms and sponsors can register with a code.
Not from one of those, but are interested in participating in STAC events and networking with senior financial technologists? Let's talk!


Topics tend to cluster in three areas:

  • Quant technology. Architectures for big data and big compute workloads such as AI (ML & DL) model training, strategy research & backtesting, tick analytics, alt data processing, market and credit risk, portfolio optimization, fraud detection, and compliance.
  • Low-latency infrastructure. Architectures for fast decision making and trade execution, primarily in automated trading. Networks, FPGA, servers, software, and other technologies for market data, trading and matching algorithms, execution, and trade-time risk.
  • Command and control. Monitoring of trade flows, time synchronization, and orchestration and management of on-prem and cloud-based infrastructure.

We're currently putting together the agenda for this event.
To see agendas from past STAC Summits, click here.

 

About STAC Events & Meetings

STAC events bring together CTOs and other industry leaders responsible for solution architecture, infrastructure engineering, application development, machine learning/deep learning engineering, data engineering, and operational intelligence to discuss important technical challenges in finance.

Sponsors

 

PLATINUM SPONSORS




GOLD SPONSORS







Exhibitors

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